seasonofbirthandexceptionallongevity:comparativestudyof...

SAGE-Hindawi Access to ResearchJournal of Aging ResearchVolume 2011, Article ID 104616, 11 pagesdoi:10.4061/2011/104616

Research Article

Season of Birth and Exceptional Longevity: Comparative Study ofAmerican Centenarians, Their Siblings, and Spouses

Leonid A. Gavrilov and Natalia S. Gavrilova

Center on Economics and Demography of Aging, NORC at the University of Chicago, 1155 East 60th Street,Chicago, IL 60637, USA

Correspondence should be addressed to Leonid A. Gavrilov, [email protected]

Received 18 February 2011; Revised 11 August 2011; Accepted 30 September 2011

Academic Editor: Peter Martin

Copyright © 2011 L. A. Gavrilov and N. S. Gavrilova. This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work isproperly cited.

This study explores the effects of month of birth (a proxy for early-life environmental influences) on the chances of survivalto age 100. Months of birth for 1,574 validated centenarians born in the United States in 1880–1895 were compared to thesame information obtained for centenarians’ 10,885 shorter-lived siblings and 1,083 spouses. Comparison was conducted using awithin-family analysis by the method of conditional logistic regression, which allows researchers to control for unobserved sharedchildhood or adulthood environment and common genetic background. It was found that months of birth have significant long-lasting effect on survival to age 100: siblings born in September–November have higher odds to become centenarians comparedto siblings born in March. A similar month-of-birth pattern was found for centenarian spouses. These results support the idea ofearly-life programming of human aging and longevity.

1. Introduction

Studies of centenarians (persons living to age 100 and over)are useful in identifying factors leading to long life andavoidance of fatal diseases. These studies may be a sensitiveway to find genetic, familial, environmental, and life-coursefactors associated with lower mortality and better survival [1,2]. Several theoretical concepts suggest that early-life eventsand conditions may have a significant long-lasting effect onsurvival to advanced ages. These concepts include (but arenot limited to) the idea of fetal origin of adult diseases alsoknown as the Barker hypothesis [3, 4] and the related ideaof early-life programming of aging and longevity; the theoryof technophysio evolution [5], the reliability theory of aging,and the high initial damage load (HIDL) hypothesis in par-ticular [6, 7]. These ideas are supported by the studies sug-gesting significant effects of early-life conditions on late-lifemortality [3, 8–10]. Finch and Crimmins [11] suggested thathistorical decline in chronic inflammation (due to decreasingexposure to early-life infections) has led to a decrease inmorbidity and mortality from chronic conditions at old age.

They showed that both childhood mortality and cardio-vascular diseases of old age may share common infectiousand inflammatory causes rooted in the external environment[12].

Month of birth often is used by epidemiologists as aproxy characteristic for environmental effects acting duringin-utero and early infancy development. These early effectsinclude temperature and sun exposure during in-utero andearly postnatal period, nutritional status during early devel-opment, exposure to infectious agents, and other factors [3,13, 14]. Previous studies demonstrated that life expectancymay be influenced by person’s month of birth [15–18]. How-ever, studies of month-of-birth effects on longevity face sig-nificant difficulties in finding appropriate data on differentialmortality by season of birth. Longitudinal data with informa-tion about season of birth are the optimal data for study ofmonth-of-birth effects on longevity [19]. Such longitudinaldata were available for population of Denmark and showedthat the remaining life expectancy at age 50 was higher forpersons born in October-November compared to personsborn in April–June [15]. In other studies, the effects of

2 Journal of Aging Research

month of birth on late-life mortality were estimated indi-rectly using information on mean age at death from cross-sectional collection of death certificates [19–22].

Little information is available on the month of birthassociation with exceptional longevity. To our knowledge,there is only one study that examines the effects of monthof birth on longevity [23]. In this study, month-of-birthdistribution of 925 age-validated German semi-supercente-narians (persons aged 105+ years) was compared to seasonaldistribution of births in the German Empire at the timeof semi-supercentenarians’ birth (1880–1900). It was foundthat more semi-supercentenarians than expected were bornin December while the proportion of semi-supercente-narians born in June was low. This study suggests that theDecember-born have a significantly higher risk of survivingup to age 105+ compared to the June-born [23] although itcannot be indicated unequivocally if month-of-birth patternamong semi-supercentenarians is due to seasonality of infantmortality or later-life month-of-birth effects. Additionalproblems in the studies of month-of-birth effects on longev-ity arise from possible confounding due to between-familyvariation in childhood socioeconomic conditions [24–26]and parental genetic background [27]. One possible solutionto these challenges is to compare associations within sibshipstaking into account that socioeconomic and genetic back-ground is similar for siblings from the same family [14, 28].

In this study, we analyze the effects of month of birthon survival to age 100 years using a large set of centenar-ians born in the United Sates in 1880–1895 and theirshorter-lived siblings and spouses. Siblings share early child-hood conditions including parental socioeconomic status,genetic background, and geographical location while spousesshare common adulthood environment. It was shown thatlongevity has a significant familial component [29–32] sug-gesting the need to control for this important factor. Com-paring month-of-birth characteristics of adult siblings orspouses with that of centenarians provides an opportunityfor obtaining net effects of month-of-birth on survival andcontrol for unobserved confounding factors.

2. Methods

2.1. Data Collection. This study compares centenarians totheir shorter-lived siblings (who share common childhoodconditions and genetic background) and spouses (whoshare common adulthood environment) using a large set ofcomputerized family histories. Family histories (genealogies)proved to be a useful source of information for studies in his-torical demography [33] and biodemography [34, 35]. In thisstudy, data were collected through a search of over 400,000online family histories available at Rootsweb (http://wc.rootsweb.ancestry.com), which is one of the largest pub-licly available repositories of online genealogies. Search forcentenarians in the Rootsweb database was conducted withassistance of the web-automation technique [36], whichallows researchers to run automated queries (using programscripts in PHP language) and search online databases forindividuals with desired properties (persons who lived 100+years in our case). Applying this technique helps researchers

to save time and effort on routine data collection from onlineresources. Application of the web-automation technique tothe Rootsweb publicly available online resource identifiedover 40,000 records of centenarians born in 1880–1895 withknown names of their parents. However, in many cases, oneand the same centenarian appeared in two or more genealo-gies. After removing these duplicates, we obtained 23,127records for centenarians born in 1880–1895 with detailedinformation on their birth and death dates as well as birthand death dates of their parents. According to the pastexperience with computerized genealogies [34], availabilityof detailed information on vital events ensures a good qualityof collected genealogies. However, a significant proportionof records for siblings in the obtained genealogies did notcontain information about death dates that we needed forthe within-family analysis of human longevity. So the nextstep was to indentify the most informative families withcomplete information on birth and death dates for siblings.As a result of this identification procedure, we found 2,834families where information on birth and death dates wasknown for more than 80 percent of siblings in a family.This procedure resulted in a set of families having higher-than-average sibship size and hence providing more con-trol records (siblings) for the matched case-control study.During this data refining procedure, the proportion of malecentenarians in genealogies dropped from 28.2% to 23.2%(see Table 1) and became close to the proportions reportedin the USA censuses (19.3–24.0%) [37], which indicates animprovement in quality for the selected genealogies.

2.2. Data Verification. Previous studies demonstrated thatage misreporting and age exaggeration in particular are morecommon among long-lived individuals [38, 39]. Therefore,the primary focus of data cleaning in this study was on theage verification for long-lived individuals. We followed theapproach of age verification and data linkage [38, 40], whichwe applied previously on another dataset of centenarians[41]. This approach involves data consistency checks, deathdate verification through the linkage to the Social SecurityAdministration Death Master File (DMF) and birth dateverification through the linkage to early USA censuses.DMF is a publicly available data resource (available at theRootsweb.com website), which covers deaths that occurredin the period 1937–2010 and captures about 95% of deathsrecorded by the National Death Index [42]. More detailsabout the procedure of centenarian age validation werepublished elsewhere [41]. Validation of centenarian deathand birth dates produced 1,574 centenarians. Informationon siblings and spouses of validated centenarians was col-lected using the web-automation technique described earlier.Table 1 shows the steps of data collection and cleaningfor this study. Note that the proportion of males amongvalidated centenarians found in genealogies (23%) is close tothe official reports (19–24%) for centenarians in the UnitedStates based on the census data [37].

We used only those records of centenarians whose agewas successfully confirmed through the DMF (with matchedbirth and death years). We added only few cases where deathyear was different from that found in the DMF (however,

Journal of Aging Research 3

Table 1: Number of centenarians and their siblings at different stages of data collection and cleaning.

Type of recordsCentenarians

Number of shorter-lived siblingsMales Females Total

All initial nonduplicate records for centenarians bornin 1880–1895 with names of parents available

7,174 18,277 25,451

Centenarians having detailed information on birth anddeath dates of their parents

6,370 16,757 23,127 172,091

Centenarians having detailed information on birth anddeath dates of their parents and siblings

707 2,127 2,834 21,893

Centenarians after data cleaning with confirmed deathdates through the linkage to DMF

365 1,209 1,574 10,885

in these cases, the individual still had a centenarian status).Our previous work with centenarian data cleaning showedthat incorrect death dates was the main source of errors ingenealogical records of centenarians [41]. At the same time,birth dates were correctly reported in practically all recordsthat had correct death dates and good consistency of birthand death dates for parents and siblings. Therefore, in thisstudy we conducted a birth date verification procedure for aportion of approximately 15% of records. In all cases, birthyears of centenarians agreed well with information reportedin 1880, 1900, or 1910 censuses (as well as information aboutbirth years of siblings). In addition to that, partial verificationof centenarian birth dates was already accomplished throughthe linkage to DMF.

As a result of data quality checks, we found 1,574 recordsof centenarians born in 1880–1895 with verified birth anddeath dates. Given the fact that longevity is often clustered infamilies, we found other centenarians in the studied families(born outside the 1880–1995 time window) so that thetotal number of centenarians increased to 1,945 persons.Distribution of centenarians according to their lifespan ispresented in Table 2. Note that the majority of centenarianslived less than 103 years and there are no claims of ex-traordinary high longevity (above 112 years) in the sample.

2.3. Life Span Data Reconstruction for Siblings and Spouses.Birth dates were reconstructed for all centenarian siblingsusing information available in computerized genealogies andearly censuses. The procedure of death date verification usingDMF is not feasible for validating death dates of shorter-lived siblings or spouses (used as controls) because datacompleteness of DMF is not very high for deaths occurredbefore the 1970s [43]. State death indexes, cemetery records,and obituaries cover longer periods of time. Taking intoaccount that exact ages of death for controls (siblings) arenot particularly important for comparison (it is sufficient toassume that they lived less than 100 years), we relied on deathdate information recorded in family histories for siblingsand spouses not found in external sources. This approachwas used previously in the Utah Population Database studyfor individuals died before 1932 [30]. Death dates werereconstructed for 99.99% of siblings using the social securitydeath master file, state death indexes, and online genealogies(only 124 out of 13,654 cases were left unresolved).

Table 2: Distribution of centenarians born in 1880–1895, by age atdeath.

Age at deathCentenarians having siblings

Men Women Both sexes

100 132 398 530

101 92 266 358

102 52 214 266

103 43 137 180

104 16 71 87

105 18 58 76

106 9 38 47

107 2 15 17

108 0 5 5

109 1 3 4

110 0 3 3

111 0 0 0

112 0 1 1

Total: 365 1,209 1,574

2.4. Study Population. Data for 10,885 siblings of 1,574centenarians were used in this study. As a result, each case(centenarian) had about 7 control siblings on average. Thesibship size (eight siblings on average) in the studied cente-narian families is higher than the average number of childrenin American families reported by the 1900 USA Census:5.12 ± 0.01; data obtained from the 5% sample of the US1900 Census from the integrated public use microdata series(IPUMS) [44]. Larger sibship size in the centenarian familiescompared to the general population can be explained by thefact that genealogies are more likely to be compiled for largerfamilies and that longer-lived individuals in the United Stateswere born more often in rural areas with higher fertility[41, 45]. This difference in sibship size with the generalpopulation is not critical for the within-family design of thisstudy when appropriate control group (shorter-lived siblingsraised in the same family or spouses) is selected. Table 3presents characteristics of the final sample used in this study.171 siblings and 4 centenarians had unknown month ofbirth, so their records were excluded from the statisticalanalyses. As expected, spouses have higher age at death thansiblings whose age at death was not conditioned on survival


Table 3: Characteristics of centenarians born in 1880–1895 and their siblings and spouses. Values are numbers (percentages) or means(standard deviations).

Characteristic Men Women Both Sexes

Number of records (percent)

Centenarians, total 365 (23.2) 1,209 (76.8) 1,574 (100.0)

Centenarians with spouses 231 (23.9) 737 (76.1) 968 (100.0)

Siblings of centenarians 5,731 (52.7) 5,154 (47.3) 10,885 (100.0)

Spouses of centenarians 814 (75.2) 269 (24.8) 1,083 (100.0)

Mean age at death, years (standard deviation)

Centenarians, total 101.5 (1.7) 101.8 (1.9) 101.7 (1.9)

Centenarians with spouses 101.5 (1.8) 101.8 (2.0) 101.8 (1.9)

Siblings of centenarians 62.9 (29.3) 66.1 (30.7) 64.3 (29.9)

Spouses of centenarians 72.69 (14.7) 77.8 (17.1) 73.9 (15.5)

Mean year of birth (standard deviation)

Centenarians, total 1887.0 (5.5) 1888.6 (5.5) 1888.2 (5.5)

Centenarians with spouses 1887.4 (5.0) 1888.8 (4.7) 1888.4 (4.8)

Siblings of centenarians 1888.6 (10.4) 1889.0 (10.3) 1888.8 (10.4)

Spouses of centenarians 1885.4 (7.5) 1892.2 (7.2) 1887.1 (8.0)

to ages eligible for marriage. Centenarians and siblingswere born in about the same year on average. Spouses ofmale centenarians were approximately 5 years younger andspouses of female centenarians were about 3 years older onaverage than their long-lived mates (see Table 3). 5% sampleof the US 1900 Census (with information on month of birth)was used for comparisons with the general population [44].

2.5. Research Design. This study explored the effects ofmonth of birth on the likelihood of survival to age 100.Centenarians (cases) were compared to their “normal”shorter-lived siblings (controls) or spouses using a within-family analysis. This approach allows investigators to studythe within-family differences, not being confounded by thebetween-family variation. Long-lived persons born in 1880–1895 were used as cases. Siblings were born in a wider timewindow than centenarians but on average in the same year.Taking into account relatively high child mortality in the19th century, we conducted analyses with different lifespancut-offs in order to study late-life survival to advanced agesand evaluate the stability of results. The main approach usedin this study is based on the comparison of children withinrather than across families. A similar approach was appliedfor comparison of centenarians to their spouses.

2.6. Statistical Analyses. Differences in the month-of-birthdistributions between centenarians or their siblings and thegeneral population according to the 1900 US Census wereassessed with the chi-square test. Standardized residuals werecalculated in order to determine which months of birth maybe major contributors to rejection of the null hypothesis (inthe case it is rejected). When the absolute value of the residualis greater than 2.00, it indicates that it was a major influenceon a significant chi-square test statistic. The chi-square testwas also used to examine whether gender or longevity isrelated to the month of birth.

Statistical analyses of the within-family effects for 1 : nmatched study were performed using a conditional multiplelogistic regression model (fixed-effect model) to investigatethe relationship between an outcome of being a case (long-lived person) and a set of prognostic factors [46, 47].The likelihood of survival to advanced ages (to be in thecentenarian group) is used as a dependent variable andmonth of birth and gender are used as explanatory variables.All analyses were conducted using Stata statistical software,release 11 [48]. Adjustment for multiple comparisons wasconducted by the Bonferroni method. However, the Bonfer-roni adjustment is often criticized by statisticians as being tooconservative [49, 50]. A technique proposed by Benjaminiand Hochberg offers a more powerful alternative to thetraditional Bonferroni method [51]. This technique is basedon controlling the false discovery rate (FDR)—the propor-tion of significant results that are actually false positives.According to the Benjamini and Hochberg procedure, thenull hypothesis is rejected when ordered individual P values(from smallest to largest) are lower than (i/m)Q, where i isa rank of P value, m is the total number of tests, and Qis the chosen FDR. The level of FDR in the Benjamini andHochberg procedure was set to 0.10.

3. Results

Comparison of month-of-birth distributions for centenar-ians and their shorter-lived siblings with month-of-birthdistribution for persons born in 1880–1890 and enumeratedby the 1900 US Census showed statistically significant differ-ences (P < 0.001 for both centenarians and their siblings).Table 4 shows month-of-birth distribution for centenari-ans, their siblings survived to adulthood and the generalpopulation. In the case of centenarians, absolute valuesof standardized residuals exceeded the critical value of 2in six cases: there is an excess of centenarians born in


66.5

77.5

88.5

99.510

10.511

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Perc

ent

inpo

pula

tion

grou

p

Month of birth

CentenariansSiblings1900 census

Figure 1: Distribution of individuals by month of birth in percent:centenarians, their shorter-lived siblings survived to age 20 andthe USA population born in 1880–1895 according to the 1900 USCensus.

September–November and a lack of centenarians born inMarch, May, and July. Figure 1 shows that the excess ofcentenarians born in the fall months is particularly highcompared to the general population. For siblings, absolutevalues of standardized residuals exceed the critical value onlyfor May-born and December-born individuals. Overall, theseasonal pattern of births for siblings is closer to that forthe general population compared to the seasonal pattern ofbirths for centenarians (Figure 1). In the general population,more persons were born in the first half of the year (51.8%)while more centenarians were born in the second half of theyear (53.12%). Centenarian siblings occupy an intermediateposition with 49.94% being born in the first half of the year.These differences in birth seasonality (being born in the firstor the second half of a year) between centenarians and theirshorter-lived siblings (survived to age 20) are statisticallysignificant (chi-square test statistic = 5.03, df = 1; P =0.025). As shown in Table 4 and Figure 1, month-of-birthdistribution for centenarians also departs from the distri-bution of their shorter-lived siblings and this difference isstatistically significant (all siblings: chi-square test statistic =19.99, df = 11, P = 0.045; siblings survived to age 20: chi-square test statistic 19.50, df = 11, P = 0.053). At the sametime, we found no statistically significant association be-tween month of birth and gender.

To analyze the effects of month-of-birth on exceptionallongevity, which are not confounded by birth and infantdeath seasonality, childhood conditions, or genetic back-ground, a within-family study was conducted. To discrimi-nate between the effects due to differential survival early inlife from the late-life effects, we analyzed survival to age100 among siblings conditional on their survival to differentadult ages. Table 5 presents the odds ratios to become a cen-tenarian for siblings born in different months and survivedto 30, 50, and 70 years of age. These results demonstratethat persons born in September–November have significantlyhigher chances of exceptional longevity than persons bornin March. This survival advantage of persons born in the

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month of birth

0.9

1

1.1

1.2

1.3

1.4

1.5

Odd

sra

tio

P = 0.007

P = 0.022

P = 0.006

Figure 2: Month of birth and odds ratios for becoming a cen-tenarian. A within-family-study of centenarians and their siblingssurvived to age 50 (9,724 studied persons). Being born in March isused as a reference level. Unadjusted P values are shown.

fall months is consistent across different lifespan cut-offssuggesting long-lasting influence of season of birth onlongevity.

Being born in the spring months was associated withdecreased chances of survival to age 100 while birth in thefall months significantly increases chances to become a cen-tenarian. Figure 2 depicts the general pattern of month-of-birth effects on longevity after age 50. This pattern suggeststhat persons born during the fall months have higher chancesof survival to age 100 compared to March-born individ-uals who have the lowest chances of achieving longevity.July-born individuals also show low odds of survival to age100 compared to individuals born in fall.

It was suggested that month-of-birth effects on mortalitymay become weaker for later-born cohorts [19]. To testwhether the season-of-birth effects are weaker in later-borncohorts, we split the sample of centenarians and siblings intotwo approximately equal groups: those who were born before1899 and those who were born after this year. The effects ofmonth-of-birth on survival after age 50 for these two cohortsare presented in Table 6. For group born before 1899, theodds of survival to 100 are significantly higher for personsborn in November compared to persons born in March. Forlater-born cohorts, the month-of-birth effect is much weakerand not statistically significant after adjustment for multiplecomparisons.

In order to control for living conditions during theadult life, we compared centenarians with their spouses.The results of these comparisons are shown in Table 7and confirm the month-of-birth pattern in longevity foundin previous analyses. Again, individuals born in October-November have a significantly higher likelihood of survival toage 100 compared to individuals born in April. These effectsare long-lasting and can be visible after age 50.

4. Discussion

4.1. Comparison with Previous Studies. We found that per-sons born in the fall months are more represented amongcentenarians compared to the general population while


Table 4: Month-of-birth distributions (in percent) for the US 1900 Census population, centenarians, and their siblingsa.

Month of birth1900 Census, 5% samplePersons born in 1880–95

Centenarians Siblings survived to age 20

N = 1,320,328 N = 1,570Standardized

residualsN = 9,175 Standardized residuals

January 9.11 8.60 −0.671 8.88 −0.721

February 8.43 8.79 0.491 8.69 0.847

March 9.51 7.77 −2.235 9.73 0.693

April 8.50 8.03 −0.645 8.33 −0.568

May 9.08 7.07 −2.643 7.44 −5.200

June 7.17 6.62 −0.808 6.87 −1.086

July 7.78 6.37 −2.004 7.57 −0.704

August 8.51 8.54 0.034 8.27 −0.780

September 8.38 10.32 2.653 8.80 1.375

October 8.24 10.25 2.781 8.74 1.672

November 7.36 9.24 2.739 7.80 1.567

December 7.92 8.41 0.687 8.87 3.240aMonth-of-birth distributions for both centenarians and their siblings differ from the month-of-birth distribution for the general population (individuals

enumerated in the 1900 census and born in 1880–1895); difference significant at P < 0.001.

Table 5: Odds ratios (P values) to become a centenarian as predicted by conditional logistic regression (fixed effects) for different age cut-offsubgroups. Effects of month of birtha.

Variable All siblingsSiblings survived to age

30Siblings survived to age

50Siblings survived to age

70

Month of birth:

January 1.13 (0.387) 1.11 (0.472) 1.11 (0.463) 1.09 (0.537)

February 1.25 (0.101) 1.25 (0.109) 1.24 (0.124) 1.16 (0.303)

March Reference Reference Reference Reference

April 1.15 (0.320) 1.15 (0.337) 1.16 (0.320) 1.09 (0.567)

May 1.20 (0.218) 1.17 (0.288) 1.19 (0.251) 1.15 (0.373)

June 1.20 (0.229) 1.00 (0.254) 1.18 (0.284) 1.11 (0.486)

July 1.03 (0.855) 1.19 (0.991) 1.01 (0.941) 1.00 (0.990)

August 1.25 (0.110) 1.24 (0.125) 1.27 (0.100) 1.21 (0.198)

September 1.44 (0.006)c 1.43 (0.009)c 1.45 (0.007)c 1.39 (0.022)

October 1.43 (0.008)c 1.37 (0.021)c 1.37 (0.022)c 1.27 (0.099)

November 1.51 (0.003)b,c 1.48 (0.005)c 1.47 (0.006)c 1.41 (0.017)

December 1.17 (0.266) 1.13 (0.380) 1.17 (0.283) 1.11 (0.486)

Female sex 3.77 (<0.001) 3.82 (<0.001) 3.80 (<0.001) 3.41 (<0.001)

Pseudo R2 0.0811 0.0861 0.0871 0.0766

Number of observations 12,132 10,393 9,724 8,123aStatistically significant effects (P < 0.05) are highlighted in bold.

bStatistically significant after Bonferroni adjustment.cStatistically significant after Benjamini-Hochberg procedure.

persons born in the first half of the year are less representedamong the group of long-lived individuals. Centenarians,their siblings, and the general population show decreasedproportion of persons born during the summer months,which is probably related to seasonal distributions of births

and infant deaths in the past [52]. The month-of-birthpattern among centenarians in this study is compared to themonth-of-birth distribution of persons aged 5–20 years inthe US 1900 Census and hence the results of this comparisonare not affected by seasonal distribution of infant deaths.


Table 6: Odds ratios (P values) to become a centenarian as pre-dicted by conditional logistic regression (fixed effects), by differentbirth cohort subgroups for siblings survived to age 50. Effects ofmonth of birtha.

Variable Born before 1889 Born in 1889 or later

Month of birth:

January 1.42 (0.109) 0.90 (0.628)

February 1.41 (0.118) 1.02 (0.911)

March Reference Reference

April 1.09 (0.717) 1.18 (0.467)

May 1.27 (0.312) 0.86 (0.500)

June 1.30 (0.289) 1.35 (0.192)

July 1.14 (0.579) 1.00 (0.984)

August 1.19 (0.446) 1.23 (0.360)

September 1.31 (0.209) 1.55 (0.042)

October 1.61 (0.027) 1.13 (0.578)

November 1.78 (0.008)b 1.23 (0.357)

December 1.33 (0.185) 0.94 (0.772)

Female sex 3.32 (<0.001) 4.74 (<0.001)

Pseudo R2 0.0842 0.1249

Number ofobservations

3,279 3,441

aStatistically significant effects (P < 0.05) are highlighted in bold.

bStatistically significant after Benjamini-Hochberg procedure.

Table 7: Odds ratios (P values) to become a centenarian as pre-dicted by conditional logistic regression (fixed effects), by differentage cut-off and gender subgroups for spouses of centenarians.Effects of month of birtha.

Variable All spousesSpouses survived to

age 50

Month of birth:

January 1.27 (0.358) 1.29 (0.346)

February 1.65 (0.066) 1.83 (0.032)

March 1.58 (0.084) 1.65 (0.067)

April Reference Reference

May 1.37 (0.263) 1.46 (0.190)

June 1.46 (0.176) 1.63 (0.099)

July 1.61 (0.096) 1.66 (0.086)

August 1.52 (0.117) 1.56 (0.112)

September 1.58 (0.079) 1.66 (0.063)

October 2.17 (0.004)b,c 2.24 (0.004)b,c

November 2.22 (0.003)b,c 2.22 (0.004)b,c

December 1.21 (0.487) 1.32 (0.332)

Female sex 3.40 (<0.001) 3.42 (<0.001)

Pseudo R2 0.2192 0.2226

Number ofobservations

1,921 1,800

aStatistically significant seasonal effects (P < 0.05) are highlighted in bold.

bStatistically significant after Bonferroni adjustment.cStatistically significant after Benjamini-Hochberg procedure.

In the previous study of German semi-supercentenarians,seasonal distribution of birth dates of long-lived individuals

was compared to the seasonal distribution of births 105years earlier, so this comparison may be influenced byseasonality of infant deaths in the past. At the same time,our results demonstrate some similarity with the results ofsemi-supercentenarian study: persons born in the secondhalf of the year are over-represented among German semi-supercentenarians [23] as it was shown in this study. Thewithin-family multivariate analysis demonstrated a survivaladvantage of individuals born in September–Novembercompared to individuals born in March. A similar patternof season-of-birth and longevity was also found for spousesof centenarians, which reinforces the findings obtained forcentenarian siblings. These results are in agreement withprevious publications on the effects of month-of-birth onlifespan in the countries of the Northern hemisphere [15, 16,21, 22, 53] and in the United States in particular [19, 54].These earlier studies show better survival for persons bornin September–December compared to persons born in themiddle of the year.

At the same time, the results of this study show thatindividuals born in March or April have similar low odds ofachieving longevity as individuals born during the summermonths and persons born during the winter months do notlive longer than the March-born individuals. This is differentfrom the results of other studies, which showed decline inmean age at death for persons born during the summermonths and relatively high mean age at death for personsborn during the winter months [19, 21, 22]. These differ-ences in month of birth pattern between our study andother publications can be partially explained by changes inseasonality of births and infant deaths over time. Birthsusually peak in March and hence March-born individuals areoverrepresented among both living and dead persons (thisis the reason why March-born individuals are highly repre-sented in the general population, see Figure 1). Studies basedon the analysis of cross-sectional death certificates do nothave information about population at risk [19] and hencemay be affected by secular changes in seasonality of birthsand infant deaths. Although these secular effects probably donot significantly modify the overall month-of-birth patternin life expectancy, they can affect amplitudes of seasonaleffects for specific months. It would be reasonable to suggestthat decline of summer infant deaths over time resulted inincreased representation of summer-born individuals in thelater-born cohorts, which led to an apparent drop in themean age at death for persons born in these months.

Study of the earlier-born and the later-born groups foundthat the season-of-birth effects fade in the later born cohorts(Table 6), which is consistent with previous reports [19] andcan be explained by improving nutrition and sanitation overtime. We found no gender differences in month-of-birthdistributions for both centenarians and their siblings, whichis consistent with previous publications [19].

It should be noted that another study of season-of-birtheffects on life span in the single-year USA birth cohorts(based on the USA Social Security Administration data)found that life expectancy at age 80 depends on monthof birth [54]. In this study, 80-year olds born in May-June showed significantly lower life expectancy compared to


individuals born in the end of the year and this seasonal pat-tern repeats itself in every studied birth cohort. This month-of-birth pattern of life expectancy is similar to the patternreported earlier for mean age at death obtained on the basisof the USA death certificates [19]. However, in the studyof centenarians and their siblings, we do not find a specificsurvival advantage for persons born in the winter months. Itis possible that certain unobserved socioeconomic or othercharacteristics of parents (such as possible preferential winterbirths for wealthier social groups), which are controlled forin the case-sibling design of our study, may result in appar-ently better survival of winter-born individuals in the generalpopulation. Further research is needed for better explanationof this phenomenon.

4.2. Strengths and Limitations. Our within-family study fol-lows centenarians and their siblings from birth until the endof their life while previous studies analyzed a cross-sectionalsample of the USA death certificates for persons belongingto multiple birth cohorts. For this reason, our results do notdepend on the secular changes in seasonality of births andinfant deaths. Another advantage of this study is its within-family design, which controls for unobserved characteristicsof childhood conditions and parental genetic background.This study confirms the existence of month-of-birth effectson longevity and shows that these effects can be observedeven after controlling for unobserved between-family vari-ation.

Some limitations of this study should be mentioned. Dueto the data collection from computerized genealogies, wecannot be certain that centenarians (and controls) representa random population sample. This limitation is not crucialfor the analytical approach applied in this study, which testsspecific hypothesis of seasonal birth effects on longevity, butmay pose a question about generalizability of results. It isbelieved that the RootsWeb source of online family historieshas more individuals with larger families and better offspringsurvival. Indeed our sample of centenarians has largerfamilies compared to the general population. This deviationfrom the general population may potentially affect the resultsof univariate analyses when month-of-birth distributions forcentenarians and siblings are compared to the general pop-ulation. However, in the within-family analyses, we comparesiblings with each other rather than with the general popula-tion, so the difference in family size does not affect the resultsof hypothesis testing about the month-of-birth effects onlongevity [55]. Also, comparison with the general populationshows better similarity of month-of-birth pattern for siblingsrather than centenarians suggesting that shorter-lived sib-lings are closer to the general population in terms of month-of-birth distribution.

Another problem is that some month-of-birth effectsbecome not statistically significant after adjustment formultiple comparisons. For example, month-of-birth effectsbecome nonsignificant when survival of siblings after age 70is studied. However, the overall pattern of month-of-birtheffects on longevity shows consistency across different agecut-offs suggesting a stability of the observed seasonalpattern. In addition to that, independent analyses on cen-

tenarian spouses demonstrated a similar pattern of month-of-birth effects on longevity. Finally, the conditional logisticregression analyses suggest that despite significant effects ofmonths of birth on relative survival the effect sizes of month-of-birth effects on survival to 100 are small and explainabout 2% of the variance of becoming a centenarian. Thissmall percentage of explained variance is related to very highvariability of individual lifespan, which has a substantialstochastic component [6].

4.3. Existing Explanations of Month-of-Birth

Effects on Longevity

4.3.1. Maternal and Child Nutrition in the Past. There areseveral possible explanations of why month of birth mayaffect mortality and health later in life. One explanationsuggests that nutritional status of mother during pregnancymay affect fetal development in utero [3, 56]. Nutritionaldeficiencies during early development may have long-lastingeffects on mortality later in life [3]. This explanation is sup-ported by the Ames theory [57] that micronutrient deficien-cies play a major role in DNA damaging, human aging, andpremature deaths from cancer and heart disease. Recentreview suggests that both improper diet stimulating chronicinflammation and dietary deficiencies and nutrient imbal-ances may be strong sources of mutagenesis [58]. So it is rea-sonable to hypothesize that seasonal vitamin deficiency dur-ing the critical periods of fetus and infant development mayaffect later health and longevity of the deficiency-exposedbirth cohorts.

Birth weight often serves as an indicator of nutritionalstatus during early development and was shown to be depen-dent on month of birth. For example, in Greece, infantsborn during the autumn and winter seasons of the year hadsignificantly increased birth weight and gestation age [20].Recent review of birth weight seasonality in developed coun-tries shows a tendency of infants born during the fall andwinter seasons in European countries to have higher birthweights [59]. There are also reports that premature birthsshow a slight excess of incidence during the months of June–August [60].

4.3.2. Seasonal Infections. Early seasonal impacts on subse-quent adult lifespan may include not only seasonal vitamindeficiency, but also other seasonal impacts, such as infectiousdiseases. Seasonal peaks of disease occurrence are typical formany infections [61]. The most drastic effects of infectiousagents in pregnancy, which probably represent the tip ofthe iceberg of the damage to progeny, include the following:cardiac malformation, deafness, cataracts, glaucoma, andtooth defects for the rubella virus (German measles); growthretardation, blindness, mental retardation, and deafness forcytomegalovirus; skin scarring, muscle atrophy, and mentalretardation for varicella (chickenpox) [62, 63]. It was shownthat poliovirus epidemics peak in July-August and exposureto this virus in the second trimester of gestation seem toproduce subsequent adult schizophrenia in February birthcohorts [64].


4.3.3. Environmental Temperature at Birth and Conception.Effect of environmental temperature during the time of birthor conception may be another possible explanation for lowproportion of centenarians among individuals born duringthe summer and spring months. For example, British womenexperiencing higher summer temperatures during theirfirst year of life and hence suffering severe diarrhea anddehydration in infancy had higher blood pressure at olderages [65]. High ambient temperature was also associatedwith higher risk of preterm delivery in the recent study of alarge sample of California births [66]. There are reports thathigh temperatures may be implicated in lower sperm quality[67, 68], particularly among smokers [69]. This may resultin a less viable progeny born during the spring months. Onthe other hand, cold outdoor temperature at birth duringthe winter months is associated with coronary heart disease,insulin resistance, and poor lung function at older age [70].

4.3.4. The Deadline Hypothesis. It was suggested that schoolsor other professional training organizations, which have adeadline for admission, may favor children who are some-what older compared to their peers (usually children bornin the fall months). This so-called deadline hypothesis [19]predicts that the relative advantage in school achievement hascumulative effects over the life course. In the case of historicaldata, the deadline hypothesis should be more relevant tosurvival of men whose social status is dependent on theirown achievements. For women, their social status in thepast was predominantly determined by the social status oftheir husbands. In the case of centenarians, who are pre-dominantly women, the deadline hypothesis looks like a lesslikely explanation of the observed month-of-birth effects onlongevity.

4.4. Explanation of Survival Advantage for Persons Born in theFall Months. Analysis of the existing literature suggests thatpersons born in the fall months in the United States couldavoid extremes of very high and very low ambient temper-atures during their first month of life as well as high sum-mer temperatures during conception. Persons born duringthe fall months also did not experience an early exposureto infectious diseases, which were common during summer,early winter, or spring months in the past. Seasonal pattern ofthe USA mortality for children below age one month in thepast supports this suggestion. According to the USA statistics,mortality below age one month in 1940 was the lowest inSeptember–November [52] suggesting lower infectious loadduring this period of the year, because most infant deaths inthe past were caused by infections. Better maternal nutritionduring the last trimester of pregnancy also contributed tothe survival advantage of individuals born during the fallseason. All these three factors (mild ambient temperatures,better maternal nutrition, and low infectious load) helpedpersons born in the fall months to avoid accumulationof excessive number of defects by body systems very earlyin life. These results are consistent with the high initialdamage load (HIDL) hypothesis [6, 7], which emphasizesthe importance of the initial level of damage in determining

future human longevity. More specific explanation of theobserved month-of-birth effects on longevity can be pro-vided by the inflammation hypothesis suggested by Finchand Crimmins [11]. According to this hypothesis, a strongacute-phase inflammatory response to childhood infectionsinitiates chronic inflammation, which promotes chronicdiseases of aging. Reduced lifetime exposure to infection andsubsequent inflammation may explain both declining mor-tality at older ages and decreasing amplitude of month-of-birth effects on lifespan over time. The results obtained inthis study suggest that optimizing the process of early devel-opment can potentially result in avoiding many diseases inlater life and significant extension of healthy life span. Moreresearch is needed to determine more specific factors ofseasonal birth effects on longevity.

5. Conclusions

This is the first study of association between month ofbirth and exceptional longevity, which controls for early-life shared conditions and common genetic background.We developed a large sample of validated centenarians,their siblings, and spouses to study early-life seasonal effectson human longevity. We found significant associationsbetween month of birth and longevity: individuals born inSeptember–November have higher likelihood of becomingcentenarians compared to March-born individuals. Theseresults are consistent with the reports of higher life ex-pectancy for persons born in the end of the year [16, 19, 21,22] and the study of mortality after age 80 in several single-year USA birth cohorts [54]. The results of this study demon-strate that month-of-birth effects on exceptional longevitypersist after controlling for shared childhood environmentand unobserved shared characteristics of parents. Associa-tion of month-of-birth with exceptional longevity appearsto be stronger for earlier birth cohorts born before 1899.Similar month-of-birth effects on longevity were found forcentenarian spouses: individuals born in October-Novemberwere more likely to live to 100 compared to individualsborn in April. The results of this study suggest that early-life environmental conditions may have long-lasting effectson human aging and longevity.

Acknowledgments

This study was supported by the US National Institute onAging (Grant no. R01 AG028620). The authors are mostgrateful to anonymous reviewers and the editor of this specialissue, Dr. Peter Martin, for constructive criticism and usefulsuggestions.

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